Levi Wood, Ph.D. (Georgia Institute of Technology - ME)
Melissa Kemp, Ph.D. (Georgia Institute of Technology - BME)
Alicia Lyle, Ph.D. (Emory University - Cardiology)
Manu Platt, Ph.D. (Georgia Institute of Technology - BME)
Srikant Rangaraju, Ph.D. (Emory University - Neurology)
Krishnendu Roy, Ph.D. (Georgia Institute of Technology - BME)
Feedback Control of Macrophages and Microglia to Regulate Neuroinflammatory Dynamics
Chronic neuroinflammation, including activation of macrophages and microglia, is a central component and likely driver of numerous neurodegenerative diseases, such as Alzheimer’s disease. There remains a critical unmet need to actively regulate glial activity in such diseases. I hypothesize that 1) macrophages and microglia may be actively regulated to achieve desired temporal profiles of inflammatory response and 2) modulating the temporal progression of inflammatory processes using active control strategies will improve pathophysiologic conditions in disease environments. Specifically, I will regulate temporal macrophage and microglial polarization, which I will demonstrate is a controllable element of the larger immune response, to reduce gliosis, synaptic density and neuronal loss. My preliminary data in macrophages show that it is possible to define polarization response functions to exogenous stimulation, e.g., LPS, which can be quantitatively modeled using low order black-box models. This novel exogenous control methodology for regulating macrophage and microglial function will use a combination of data driven modeling and system dynamics and control theory. The black-box model enables reliable parameter estimation for predicting dynamic responses to future inputs I used the identified model as part of an open-loop control framework to tailor input sequences to obtain desired temporal trajectories of polarization. Moving forward, I will use a similar modeling framework applied to shift microglial phenotype between homeostatic, pro-inflammatory, and disease associated microglial states, recently defined by transcriptome-wide analysis. During this thesis, I will implement a closed-loop framework to regulate macrophage and microglial response in vitro. Moreover, I will develop a data-driven modeling framework to define and control temporal responses in vivo. Given the importance of dynamic pro- and anti-inflammatory activity in the AD brain, the control methodology presented here will have numerous applications for treating chronic neuroinflammatory diseases.